Statistics is the branch of mathematics that deals with real life problems. As such, it is an essential tool for economists. Unfortunately, the way the concept is introduced to students is not compatible with the way economists think and learn. The problem is worsened by the use of mathematical jargon and complex derivations. However, as this book demonstrates, neither is necessary. The book is written in simple English with minimal use of symbols, mostly for the sake of brevity and to make reading literature more meaningful. The second edition also incorporates Stata software for use by more technically oriented readers who have access to sophisticated software. The objective of this book is to address the fundamentals of statistical analysis in a simple and easy-to-comprehend way. Instead of covering numerous topics, the book covers interrelated subjects that are necessary for the comprehension of the presented topics. The second edition has augmented the explanations in the first to clarify the subjects even more. The examples are based on economic theory utilizing actual data. The hope is that the use of theory will prove useful in relating the subject to actual empirical applications and help with research.

The quick way to learn Microsoft Visio 2016!This is learning made easy. Get more done quickly with Visio 2016. Jump in wherever you need answers--brisk lessons and colorful screenshots show you exactly what to do, step by step. Get results faster with starter diagrams Diagram processes, organizations, networks, and datacenters Add styles, colors, and themes Enhance diagrams with data-driven visualizations Link to external data sources, websites, and documents Add structure to diagrams with containers, lists, and callouts Validate flowchart, swimlane, and BPMN diagrams Collaborate and publish with Visio Services and Microsoft SharePoint 2016 Look up just the tasks and lessons you need

In The Patient Revolution, author Krisa Tailor—a noted expert in health care innovation and management—explores, through the lens of design thinking, how information technology will take health care into the experience economy. In the experience economy, patients will shift to being empowered consumers who are active participants in their own care. Tailor explores this shift by creating a vision for a newly designed health care system that's focused on both sickness and wellness, and is driven by data and analytics. The new system seamlessly integrates health into our daily lives, and delivers care so uniquely personalized that no two people are provided identical treatments. Connected through data, everyone across the health care ecosystem, including clinicians, insurers, and researchers, will be able to meet individuals wherever they are in their health journey to reach the ultimate goal of keeping people healthy. The patient revolution has just begun and an exciting journey awaits us. Praise for the patient revolution "A full 50% of the US population has at least one chronic disease that requires ongoing monitoring and treatment. Our current health care system is woefully inadequate in providing these individuals with the treatment and support they need. This disparity can only be addressed through empowering patients to better care for themselves and giving providers better tools to care for their patients. Both of those solutions will require the development and application of novel technologies. In Krisa Tailor's book The Patient Revolution, a blueprint is articulated for how this could be achieved, culminating in a vision for a learning health system within 10 years." —Ricky Bloomfield, MD, Director, Mobile Technology Strategy; Assistant Professor, Duke Medicine "In The Patient Revolution, Krisa Tailor astutely points out that 80% of health is impacted by factors outside of the health care system. Amazon unfortunately knows more about our patients than we do. The prescriptive analytics she describes will allow health care providers to use big data to optimize interventions at the level of the individual patient. The use of analytics will allow providers to improve quality, shape care coordination, and contain costs. Advanced analytics will lead to personalized care and ultimately empowered patients!" —Linda Butler, MD, Vice President of Medical Affairs/Chief Medical Officer/Chief Medical Information Officer, Rex Healthcare " The Patient Revolution provides a practical roadmap on how the industry can capture value by making health and care more personalized, anticipatory, and intuitive to patient needs." —Ash Damle, CEO, Lumiata "Excellent read. For me, health care represents a unique economy—one focused on technology, but requiring a deep understanding of humanity. Ms. Tailor begins the exploration of how we provide care via the concepts of design thinking, asking how we might redesign care with an eye toward changing the experience. She does an excellent job deconstructing this from the patient experience. I look forward to a hopeful follow-up directed at changing the provider culture." —Alan Pitt, MD, Chief Medical Officer, Avizia "Whether you're a health care provider looking to gain an understanding of the health care landscape, a health data scientist, or a seasoned business pro, you'll come away with a deeper, nuanced understanding of today's evolving health care system with this book. Krisa Tailor ties together—in a comprehensive, unique way—the worlds of health care administration, clinical practice, design thinking, and business strategy and innovation." —Steven Chan, MD, MBA, University of California, Davis

This comprehensive guide to Qlik Sense provides you with everything you need to harness its data visualization capabilities effectively in your business or organization. Covering essential techniques and insights, this book focuses on understanding, implementing, and optimizing Qlik Sense for various data discovery applications. What this Book will help me do Understand the purpose and vision behind Qlik Sense and how it revolutionizes data discovery. Gain practical knowledge to manage, load, and visualize your data effectively using Qlik Sense. Learn how to administer Qlik Sense systems, ensuring secure and efficient usage. Explore extending Qlik Sense capabilities through its Dev Hub and other advanced features. Apply Qlik Sense in practical contexts, such as sales analytics, HR insights, and demographic studies. Author(s) Henric Cronström and co-authors, with vast experience directly from QlikTech International AB, bring authoritative insights into this book. Their expertise in business analytics and direct involvement with the development of Qlik Sense make this book a reliable and insightful resource for learners. Who is it for? This book is ideal for business intelligence professionals, data analysts, and decision-makers looking to maximize the potential of Qlik Sense. Whether you're new to Qlik Sense or have a general understanding of BI concepts, this guide will help you elevate your data discovery skills and apply actionable insights to real-world scenarios.

Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy! Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now. Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing. You’ll master data science by answering fascinating questions, such as: • Are religious individuals more or less likely to have extramarital affairs? • Do attractive professors get better teaching evaluations? • Does the higher price of cigarettes deter smoking? • What determines housing prices more: lot size or the number of bedrooms? • How do teenagers and older people differ in the way they use social media? • Who is more likely to use online dating services? • Why do some purchase iPhones and others Blackberry devices? • Does the presence of children influence a family’s spending on alcohol? For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon.

In just 24 lessons of one hour or less, Sams Teach Yourself R in 24 Hours helps you learn all the R skills you need to solve a wide spectrum of real-world data analysis problems. You’ll master the entire data analysis workflow, learning to build code that’s efficient, reproducible, and suitable for sharing with others. This book’s straightforward, step-by-step approach teaches you how to import, manipulate, summarize, model, and plot data with R; formalize your analytical code; and build powerful R packages using current best practices. Practical, hands-on examples show you how to apply what you learn. Quizzes and exercises help you test your knowledge and stretch your skills. Learn How To Install, configure, and explore the R environment, including RStudio Use basic R syntax, objects, and packages Create and manage data structures, including vectors, matrices, and arrays Understand lists and data frames Work with dates, times, and factors Use common R functions, and learn to write your own Import and export data and connect to databases and spreadsheets Use the popular tidyr, dplyr and data.table packages Write more efficient R code with profiling, vectorization, and initialization Plot data and extend your graphical capabilities with ggplot2 and Lattice graphics Develop common types of models Construct high-quality packages, both simple and complex Write R classes: S3, S4, and Reference Classes Use R to generate dynamic reports Build web applications with Shiny Register your book at informit.com/register for convenient access to updates and corrections as they become available. This book’s source code can be found at http://www.mango-solutions.com/wp/teach-yourself-r-in-24-hours-book/.

Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.

Describes the basics of using the SQL procedure and provides comprehensive reference information. The usage information includes retrieving data from single and multiple tables; selecting specific data from tables; subsetting, ordering, and summarizing data; updating tables; combining tables to create new tables and useful reports; performing queries on database management system (DBMS) tables; using PROC SQL with the SAS macro facility; and debugging and optimizing PROC SQL code. The reference information includes statements, dictionary components, and system options.

Written by a leading contributor to volatility modeling and Risk's 2009 Quant of the Year, this book explains how stochastic volatility is used to tackle practical issues arising in the modeling of derivatives. With many unpublished results and insights, the book addresses the practicalities of modeling local volatility, local-stochastic volatility, and multi-asset stochastic volatility. It covers forward-start options, variance swaps, options on realized variance, timer options, VIX futures and options, and daily cliquets.

More and more organizations around the globe are expecting that professionals will make data-driven decisions. Employees, team leaders, managers, and executives that can think quantitatively should be in high demand. The goal of this book is to increase ability to identify a problem, collect data, organize, and analyze data that will help aid in making more effective decisions. This book will provide you with a solid foundation for thinking quantitatively within your company. To help facilitate this objective, this book follows two fictitious companies that encounter a series of business problems, while demonstrating how managers would use the concepts in the book to solve these problems and determine the next course of action. This book is for beginners and does not require prior statistical training. All computations will be completed using Microsoft Excel.

The technique of regression analysis is used so often in business and economics today that an understanding of its use is necessary for almost everyone engaged in the field. This book covers essential elements of building and understanding regression models in a business/economic context in an intuitive manner. The book provides a non-theoretical treatment that is accessible to readers with even a limited statistical background. This book describes exactly how regression models are developed and evaluated. The data used in the book are the kind of data managers are faced with in the real world. The book provides instructions and screen shots for using Microsoft Excel to build business/economic regression models. Upon completion, the reader will be able to interpret the output of the regression models and evaluate the models for accuracy and shortcomings.

Students and instructors of statistics courses using SAS University Edition will welcome this book. Learning fundamental statistics is essential to solving problems with SAS. Essential Statistics Using SAS University Edition demonstrates how to use SAS University Edition to apply a variety of statistical methodologies, from the simple to the not-so-simple, to a range of data sets. Learn how to apply the appropriate statistical method to answer a particular question about a data set, and correctly interpret the numerical results that you obtain. SAS University Edition users who are new to SAS or who need a refresher course will benefit from the statistics overview and topics, such as multiple linear regression, logistic regression, and Poisson regression.

THE DEFINITIVE GUIDE TO NEXTGENERATION DIGITAL MEASUREMENT: INDISPENSABLE INSIGHT FOR BUILDING HIGH-VALUE DIGITAL EXPERIENCES! Helps you capture the knowledge you need to deliver deep personalization at scale Reflects today’s latest insights into digital behavior and consumer psychology For every digital marketer, analyst, and executive who wants to improve performance To win at digital, you must capture the right data, quickly transform it into the right knowledge,and use them both to deliver deep personalization at scale. Conventional digital metrics simply aren’t up to the task. Now, Gary Angel shows how to reinvent digital measurement so it delivers all you need to create richer, more compelling digital experiences. For more than a decade, Angel has helped leading global enterprises succeed at digital. This book reflects all he’s learned. You’ll find valuable guidance on understanding visitor intent… creating customer taxonomies… digital segmentation… integrating VoC research… and using behavioral analysis and controlled experiments to investigate what drives customer choice. Angel will help you measure the value of every digital interaction more accurately, identify specific digital behaviors that predict success, and create a comprehensive measurement paradigm that integrates all your digital spaces. With flawed tools and siloed analytics, you’re blind to what’s really happening online. But you don’t have to be. Gary Angel will help you make the invisible visible… actionable… profitable. Most common digital metrics are virtually useless. They measure the wrong things in the wrong ways. They don’t link digital activity to customer attitudes and behaviors. They don’t work well with today’s powerful analytics tools. Above all, they don’t help you improve your performance. Angel shows how to transform “raw facts” about digital behavior into meaningful knowledge about your visitors… what they were trying to accomplish…how well you helped them… how you can personalize and optimize their digital experiences from now on… how you can use measurement to provide deep personalization at scale. More rigorous, integrated, and usable than any competitive book, Measuring the Digital World will help you create, deliver, and consume digital information with unprecedented sophistication. Whether you’re a digital analyst, marketer, user experience designer, or executive, you’ll find it indispensable. Why conventional digital metrics are arbitrary and misguided Refocus on what you need to know, not what you don’t Capture the “why” Integrate VoC research and behavioral data to build better, richer, more accurate segments Go beyond snapshots: understand your customer’s entire digital experience Understand how your customers’ views and behaviors evolve over time Segment in three dimensions for a multichannel world Treat each channel as part of a larger, integrated, sequential journey

Get the tools you need to use SAS® in clinical trial design!

Unique and multifaceted, Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods, edited by Sandeep M. Menon and Richard C. Zink, thoroughly covers several domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods that are applicable to and widely used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, the book touches on a wide variety of topics, including dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs that incorporate historical data; adaptive sample size re-estimation; adaptive randomization to allocate subjects to more effective treatments; and population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology, and rheumatology. Individual chapters are authored by renowned contributors, experts, and key opinion leaders from the pharmaceutical/medical device industry or academia. Numerous real-world examples and sample SAS code enable users to readily apply novel clinical trial design and analysis methodologies in practice.

"Mastering RStudio: Develop, Communicate, and Collaborate with R" is your guide to unlocking the potential of RStudio. You'll learn to use RStudio effectively in your data science projects, covering everything from creating R packages to interactive web apps with Shiny. By the end, you'll fully understand how to use RStudio tools to manage projects and share results effectively. What this Book will help me do Gain a comprehensive understanding of the RStudio interface and workflow optimizations. Effectively communicate data insights with R Markdown, including static and interactive documents. Create impactful data visualizations using R's diverse graphical systems and tools. Develop Shiny web applications to showcase and share analytical results. Learn to collaborate on projects using Git and GitHub, and understand R package development workflows. Author(s) Julian Hillebrand and None Nierhoff are experienced R developers with years of practical expertise in data science and software development. They have a passion for teaching how to utilize RStudio effectively. Their approach to writing combines practical examples with thorough explanations, ensuring readers can readily apply concepts to real-world scenarios. Who is it for? This book is ideal for R programmers and analysts seeking to enhance their workflows using RStudio. Whether you're looking to create professional data visualizations, develop R packages, or implement Shiny web applications, this book provides the tools you need. Suitable for those already familiar with basic R programming and fundamental concepts.

This book describes state-of-the-art optimization techniques used to solve problems with adaptive, dynamic, and stochastic features. It presents modern advances in static and dynamic optimization, decision analysis, intelligent systems, evolutionary programming, heuristic optimization, stochastic and adaptive dynamic programming, and adaptive critics. It evaluates optimization methods for handling operational planning, Voltage/VAr, control coordination, vulnerability, reliability, resilience, and reconfiguration issues, providing mathematical formulations, algorithms for implementation, examples, and case studies. It also discusses the limitations of current optimization techniques in meeting the challenges of smart electric grids.

Offering a planned approach for determining cause and effect, DOE Simplified: Practical Tools for Effective Experimentation, Third Edition integrates the authors’ decades of combined experience in providing training, consulting, and computational tools to industrial experimenters. Supplying readers with the statistical means to analyze how numerous variables interact, it is ideal for those seeking breakthroughs in product quality and process efficiency via systematic experimentation. Following in the footsteps of its bestselling predecessors, this edition incorporates a lively approach to learning the fundamentals of the design of experiments (DOE). It lightens up the inherently dry complexities with interesting sidebars and amusing anecdotes. The book explains simple methods for collecting and displaying data and presents comparative experiments for testing hypotheses. Discussing how to block the sources of variation from your analysis, it looks at two-level factorial designs and covers analysis of variance. It also details a four-step planning process for designing and executing experiments that takes statistical power into consideration. This edition includes a major revision of the software that accompanies the book (via download) and sets the stage for introducing experiment designs where the randomization of one or more hard-to-change factors can be restricted. Along these lines, it includes a new chapter on split plots and adds coverage of a number of recent developments in the design and analysis of experiments. Readers have access to case studies, problems, practice experiments, a glossary of terms, and a glossary of statistical symbols, as well as a series of dynamic online lectures that cover the first several chapters of the book.

Creating Data Stories with Tableau Public is a comprehensive guide to building impactful and interactive data visualizations using Tableau Public. Whether you are an investigative journalist, blogger, or data enthusiast, this book takes you through all the essential concepts, from connecting to data sources to publishing your visualizations online. You will learn how to effectively communicate data-driven stories with engaging visuals. What this Book will help me do Understand how to connect and prepare data for Tableau Public visualizations, including tips on cleaning and joining data. Learn about various chart types and their applications to visualize data effectively according to context and message. Discover methods for creating geographic maps and adding meaningful calculations to enhance your visualizations. Master the art of designing dashboards and storytelling with interactive elements like filters and actions. Gain insights on how to publish and embed your Tableau Public visualizations to share your data stories with wider audiences. Author(s) None Ohmann is an accomplished author and educator with rich expertise in data visualization and storytelling. Leveraging a passion for effective communication, None has written extensively on using tools like Tableau Public to bring data to life. As an advocate for accessible and interactive visualizations, None's work bridges technical proficiency and creative expression. Who is it for? This book is perfect for investigative journalists, bloggers, and media professionals eager to incorporate data visualizations into their work. Whether you're a beginner or have some experience with Tableau Public, you'll find practical advice to enhance your abilities. Organizations and teams that deal with data storytelling will also benefit from the clear and actionable strategies outlined in this guide.

This book covers the practical aspects of database design, data cleansing, data analysis, and data protection , among others. The focus is on what you really need to know to create the right database for your small business and to leverage it most effectively to spur growth and revenue. Databases for Small Business is a practical handbook for entrepreneurs, managers, staff, and professionals in small organizations who are not IT specialists but who recognize the need to ramp up their small organizations’ use of data and to round out their own business expertise and office skills with basic database proficiency. Anna Manning—a data scientist who has worked on database design and data analysis in a computer science university research lab, her own small business, and a nonprofit—walks you through the progression of steps that will enable you to extract actionable intelligence and maximum value from your business data in terms of marketing, sales, customer relations, decision making, and business strategy. Dr. Manning illustrates the steps in the book with four running case studies of a small online business, an engineering startup, a small legal firm, and a nonprofit organization.

Learn from state-of-the-art examples in robotics, motors, detection filters, chemical processes, aircraft, and spacecraft. This is a practical reference for industry engineers using MATLAB to solve everyday problems. With MATLAB Recipes: A Problem-Solution Approach you will review contemporary MATLAB coding including the latest language features and use MATLAB as a software development environment including code organization, GUI development, and algorithm design and testing. This book provides practical guidance for using MATLAB to build a body of code you can turn to time and again for solving technical problems in your line of work. Develop algorithms, test them, visualize the results, and pass the code along to others to create a functional code base for your firm.

TO BUILD WINNING TEAMS AND SUCCESSFUL SPORTS BUSINESSES, GUIDE YOUR DECISIONS WITH DATA This up-to-the-minute reference will help you master all three facets of sports analytics – and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations—not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R and Python code, interpreting your results, and more. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business. Whether you’re a team executive, coach, fan, fantasy player, or data scientist, this guide will be a powerful source of competitive advantage… in any sport, by any measure. All data sets, extensive R and Python code, and additional examples available for download at http://www.ftpress.com/miller/ This exceptionally complete and practical guide to sports data science and modeling teaches through realistic examples from sports industry economics, marketing, management, performance measurement, and competitive analysis. Thomas W. Miller, faculty director of Northwestern University’s pioneering Predictive Analytics program, shows how to use advanced measures of individual and team performance to judge the competitive position of both individual athletes and teams, and to make more accurate predictions about their future performance. Miller’s modeling techniques draw on methods from economics, accounting, finance, classical and Bayesian statistics, machine learning, simulation, and mathematical programming. Miller illustrates them through realistic case studies, with fully worked examples in both R and Python. Sports Analytics and Data Science will be an invaluable resource for everyone who wants to seriously investigate and more accurately predict player, team, and sports business performance, including students, teachers, sports analysts, sports fans, trainers, coaches, and team and sports business managers. It will also be valuable to all students of analytics and data science who want to build their skills through familiar and accessible sports applications Gain powerful, actionable insights for: Understanding sports markets Assessing players Ranking teams Predicting scores Making game day decisions Crafting marketing messages Promoting brands and products Growing revenues Managing finances Playing what-if games And much more

Contains the complete reference for all Base SAS procedures. Provides information about what each procedure does and, if relevant, the kind of output that it produces.

This guide explains how to apply health economic evaluation techniques to both clinical trial and non-clinical trial data. Through a simple, applied approach using examples and SAS software, the book helps statisticians and researchers in health economics assess cost-effectiveness. It covers trial design, case report form design, quality of life measures, sample sizes, submissions to regulatory authorities for reimbursement, Markov models, cohort models, and decision trees. Examples and case studies are provided at the end of each chapter.

This book shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on their 25 years of software development experiences, methodological research, and broad scientific collaborations to deliver a book that clearly and succinctly explains concepts and addresses real scientific questions. The book uses the authors' R package spatstat throughout to process and analyze spatial point pattern data.

Don’t let your fear of finance get in the way of your success. This digital collection, curated by Harvard Business Review, brings together everything a manager needs to know about financial intelligence. It includes Financial Intelligence, called a “must-read” for decision makers without expertise in finance; A Concise Guide to Macroeconomics, which covers the essentials of macroeconomics and examines the core ideas of output, money, and expectations; Essentials of Finance and Budgeting, which explains everything HR professionals need to know to make wise financial decisions; Ahead of the Curve, Joseph H. Ellis’s forecasting method to help managers and investors understand and predict the economic cycles that control their businesses and financial fates; Beyond Budgeting; which offers a coherent management model that overcomes the limitations of traditional budgeting; Preparing a Budget, packed with handy tools, self-tests, and real life examples to help you hone critical skills; and HBR Guide to Finance Basics for Managers, which will give you the tools and confidence you need to master the fundamentals of finance.